1. Field of the Invention
The present invention relates to a method and apparatus for motion picture estimation. More particularly, the present invention relates to shielding a user's privacy during video communications or a video call.
2. Description of the Related Art
The increased development of moving picture compression and transmission technologies has increased the popularity of video communications and/or video calls because of the ability to transmit and receive better quality communications at increasingly lower costs. Yet, there has been little progress in technically overcoming any of the adverse effects relating to the video communications. For example, a major adverse effect of the video communications is that the place where a user is located is broadcast along with his/her image, thus impairing his/her privacy because the contents of one's room (and/or the condition e.g. clean, sloppy, etc.) is often in the background of the user's image. To avert this problem and render the video communications active, a technique for distinguishing an object from a background in video communications and processing them separately is required. According to such a technique, the identified background can be replaced by another background, the place of the user is not known.
Techniques have been proposed in the art to distinguish an object from a background in a moving picture. A major technique is referred to as a Snake Algorithm that represents the boundary between an object and a background as straight lines.
The Snake Algorithm detects the contour of the object by repeatedly moving from user-input snake points toward points that minimize an energy function. To be more specific, N points are set for the silhouette of the object and N−1 straight lines sequentially connecting the N points are computed. The edge energy, elastic energy, and bend energy of the whole straight line are computed and points with a minimum sum of energies are estimated within a predetermined range. In this manner, the N points are updated repeatedly until they converge to optimal points with minimum energies. The final estimated combination of straight lines then forms the contour of the object, as the object is thereby distinguished from the background.
Therefore, the Snake Algorithm separates the object from the background by computing the energies of straight lines. Since energies are computed, optimized data can be extracted for a total of pixels. Also, with the repetition-based convergence, data is automatically achieved. However, the conventional Snake Algorithm has some shortcomings in application to video communication or video calls under a mobile environment.
First, it is difficult to determine that points with optimal edge, elastic, and bending energies form the silhouette of an object in an image with a complex background. Especially when the background has many edges and colors, silhouette extraction is much more difficult when using the Snake Algorithm. This drawback of the Snake Algorithm means that the requirement for the Snake Algorithm is a simple background for greater accuracy. This simple background requirement is a severe restriction to video communications made through a portable terminal in the mobile environment.
Moreover, the estimation of N points based on repeated computations of minimum energies requires a large volume of computation and takes a certain amount of time to complete. There are difficulties in determining the initial N points and setting the range within which the N points should be located. With the aforementioned shortcomings, the conventional Snake Algorithm is not suitable for the estimation of object contours in portable terminal-based video communications. Accordingly, there exists a need for a technique for distinguishing an object from a background, to suit portable terminal-based video communications and video calls.